Gabriel E. Cabrera Guzmán

Research

Last updated on

You can find my research statement here.

Publications

Real Estate Returns and the Macroeconomy: Insights from Big Data in the U.S., Canada, and the U.KNew!
with J. Díaz and E. Hansen · 2026
The Journal of Real Estate Finance and Economics, p.1-89.
Forecasting the Volatility of U.S. Oil and Gas Firms with Machine Learning
with J. Díaz and E. Hansen · 2025
Journal of Forecasting, vol. 44, p.1383-1402.
Time-Varying Risk Aversion and International Stock Returns
with M. Guidolin and E. Hansen · 2025
The North American Journal of Economics and Finance, vol. 75, p.102271.
Machine-Learning Stock Market Volatility: Predictability, Drivers, and Economic Value
with J. Díaz and E. Hansen · 2024
International Review of Financial Analysis, vol. 94, p.103286.
Gold Risk Premium Estimation with Machine Learning Methods
with J. Díaz and E. Hansen · 2023
Journal of Commodity Markets, vol. 31, p. 100293.
Economic Drivers of Commodity Volatility: The Case of Copper
with J. Díaz and E. Hansen · 2021
Resources Policy, vol. 73, p. 102224.
A Random Walk Through the Trees: Forecasting Copper Prices Using Decision Learning Methods
with J. Díaz and E. Hansen · 2020
Resources Policy, vol. 69, p. 101859.

Job Market Paper

When Managers Speak, Markets Listen: Price Discovery During Analyst/Investor Days
with O. Kolokolova and S. Sarah Zhang · 2026
Latest draft Oct 2026.
We study how markets incorporate information released during Analyst/Investor Days, multi-hour corporate disclosure events comprising managerial presentations and a Q&A session. Aligning sentence-timestamped transcripts with tick-level trades and quotes for 2,490 U.S. events from 2014 to 2025, we show that 80% of the event-window return is incorporated before the Q&A begins. Price adjustment occurs through both discrete jumps and gradual drift bursts. Forward-looking and future-oriented statements are associated with larger absolute returns, while jump probabilities vary systematically with disclosure content, increasing after negative-tone speech and decreasing after positive-tone speech. CEO speech is associated with larger returns and higher jump probabilities, while drift bursts show little relation to language and are strongly associated with signed order-flow imbalance. Differentiating between retail and non-retail order imbalance, we find that non-retail imbalance has the larger baseline association with drift bursts, whereas the association with retail imbalance strengthens during both presentations and Q&A.
  • How does price discovery unfold while information is being revealed during multi-hour Analyst/Investor Days?
  • Is price discovery concentrated in the scripted presentation or in the Q&A?
  • Do prices adjust through discrete revisions when informative statements are made, through gradual trading-induced adjustment as investors process information, or through both?
  • About 80% of the event-window return is incorporated before the Q&A begins, against roughly 40% for the presentation part of earnings calls.
  • Prices move while managers speak: minutes after presenter speech carry 17% larger absolute returns than silent minutes and are 26% more likely to contain a jump.
  • Jumps follow content. Forward-looking and future-oriented minutes carry the largest absolute returns, and jumps are more likely after negative-tone speech and less likely after positive-tone speech.
  • Drift bursts follow lagged signed order-flow imbalance and show little relation to language.
  • CEO speech is associated with 0.30 bp higher absolute returns and a 0.41 pp higher jump probability, with no shift in drift bursts.
  • Non-retail order flow has the larger baseline effect but changes little when managers speak. The effect of retail order flow rises by 39% during presenter speech and also rises during the Q&A.
  • The results hold for in-person and virtual events alike and outside the pandemic years.

Working Papers

Product Market Competition and Voluntary Disclosure: Evidence from Analyst/Investor Days
with O. Kolokolova and S. Sarah Zhang · 2026
Latest draft Aug 2026.
Abstract
Analyst/investor (A/I) days are a relatively new and distinct channel of firm disclosure. We show that firms are more likely to host A/I days when levels of current product market competition are low and threats from potential rivals are high—the pattern that we label “competition timing”. Such timing predicts a higher informativeness of an event, with companies emphasising innovation, forward outlooks, and firm value. It is also associated with stronger market responses, including a more positive tone of speakers, higher short-term abnormal returns, improved stock liquidity, sustained increases in institutional ownership post-event, and a subsequent drop in the pressure from potential competitors entering the same product-market space. Our results establish A/I days as a potential strategic tool for firms’ competitive positioning.
Save the Date: Analyst/Investor Days as a Trading Signal
with O. Kolokolova and S. Sarah Zhang · 2026

Work-in-Progress

Why Is 1/N So Hard to Beat? Adaptive Learning and the Limits of Dynamic Portfolio Choice
Miscalibrated or Informative? Asymmetric Forecast Uncertainty in Predictive Regressions for Stock Returns